Next-generation VOC biosensors for pest surveillance

Overview

This biosensor platform detects volatile organic compounds (VOCs) emitted by pests, providing a non-invasive and early indicator of pest presence. Conventional VOC analysis using Gas Chromatography-Mass Spectrometry (GC-MS) is costly, requires specialist expertise, and is poorly suited to continuous field deployment. This technology offers a low-cost, field-deployable alternative for real-time pest monitoring. An AI-based processing pipeline identifies pest-specific signal patterns and distinguishes them from environmental noise, improving detection reliability in the field.

Technical specifications

Core technology:

• Chemiresistive VOC biosensor based on carbon nanomaterials functionalised with a copolymer
• Laboratory-validated for 2-heptanone, a VOC associated with mammalian predator species
• Low-cost wireless data logger enables continuous field deployment
• Machine learning applied to validate sensor performance under field conditions

AI signal processing:

• Pipeline ingests sensor data and performs feature extraction
• Environmental effects such as temperature and humidity, which can obscure the analyte response, are modelled and corrected
• Output is a corrected signal that more closely reflects the sensor's measurement of the target VOC

Customisation:

• Sensor surface can be further functionalised to enhance sensitivity to specific target VOCs

Technology readiness level

The sensor platform has been validated for detection of 2-heptanone, and a wireless data logger has been developed for field deployment. Machine learning has assessed sensor performance under field conditions. Next-phase validation involves laboratory trials to calibrate the sensor for targeted VOCs through controlled exposure to pure synthetic sources and, where possible, biological sources. Direct exposure to live target insects is planned, subject to regulatory and containment approvals. Once validated, the complete system will be ready for pilot deployment in pest surveillance applications.